The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 101 8 5.5 3 12 12 7.4 6.8 4.7 50 0.0 23 0.1 3 A Click the icon to view the eritical values of the Pearson corelason coefficient e What is the regression equation? A Critical Values of the Pearson Correlation Coefficient r y=U•Lk (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 milion is million. (Round to one decimal place as needed.) . Critical Values of the Pearson Correlation Coefficientr =0.05 NOTE: To test Ha p0 against H p0. reject H. the absolute value of preater than the critical value in the table. E=0.01 in 4 0.050 0.000 0.050 0.017 0.875 0.834 0.878 0.811 0.764 0.707 0.000 0.432 0.002 0.570 Is the result elose to the actual number of viewers, 4.1 million? ris O A. The result is not very elose to the actual number of viewers of 4.1 million. OB. The result is very close to the actual number of viewers of 4.1 milion. 0.708 10 0.705 OC. The result is exacty the same as the actual number of viewers of 4.1 million. n, 11 0.735 O D. The result does not make sense given the context of the data. 12 0.708 13 0.553 0.684 0.001 14 0.532 15 0.514 0.841 0.407 10 17 0.023 0.000 0.482 18 0.468 0.500 0.675 10 0.456 20 25 30 0.444 0.300 0.301 0.661 0.505 0.403 35 40 45 50 00 0.335 0.430 0.402 0.378 0.312 0 204 0 279 0 254 0.3/2 0.381 70 80 0.330 0.305 0.200 0.236 0 220
The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) 101 8 5.5 3 12 12 7.4 6.8 4.7 50 0.0 23 0.1 3 A Click the icon to view the eritical values of the Pearson corelason coefficient e What is the regression equation? A Critical Values of the Pearson Correlation Coefficient r y=U•Lk (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $2 million? The best predicted number of viewers for a television star with a salary of $2 milion is million. (Round to one decimal place as needed.) . Critical Values of the Pearson Correlation Coefficientr =0.05 NOTE: To test Ha p0 against H p0. reject H. the absolute value of preater than the critical value in the table. E=0.01 in 4 0.050 0.000 0.050 0.017 0.875 0.834 0.878 0.811 0.764 0.707 0.000 0.432 0.002 0.570 Is the result elose to the actual number of viewers, 4.1 million? ris O A. The result is not very elose to the actual number of viewers of 4.1 million. OB. The result is very close to the actual number of viewers of 4.1 milion. 0.708 10 0.705 OC. The result is exacty the same as the actual number of viewers of 4.1 million. n, 11 0.735 O D. The result does not make sense given the context of the data. 12 0.708 13 0.553 0.684 0.001 14 0.532 15 0.514 0.841 0.407 10 17 0.023 0.000 0.482 18 0.468 0.500 0.675 10 0.456 20 25 30 0.444 0.300 0.301 0.661 0.505 0.403 35 40 45 50 00 0.335 0.430 0.402 0.378 0.312 0 204 0 279 0 254 0.3/2 0.381 70 80 0.330 0.305 0.200 0.236 0 220
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 15PPS
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Transcribed Image Text:The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $2 million. Is the result close to the actual number of viewers, 4.1 million? Use a significance level of 0.05.
8
Salary (millions of $)
Viewers (millions)
101
3
12
12
5.5
7.4
6.8
4.7
5.6
6.6
2.3
9.1
Click the icon to view the critical values of the Pearson correlation coefficient r.
What is the regression equation?
- X
Critical Values of the Pearson Correlation Coefficient r
y=+ x (Round to three decimal places as needed.)
What is the best predicted number of viewers for a television star with a salary of $2 million?
The best predicted number of viewers for a television star with a salary of $2 million is million.
Critical Values of the Pearson Correlation Coefficient r
NOTE: To test Ho: p=0
against H;: p# 0, reject H
if the absolute value of r is
greater than the critical
value in the table.
a= 0.05
= 0.01
n
(Round to one decimal place as needed.)
4
0.950
0.000
5
0.878
0.059
Is the result close to the actual number of viewers, 4.1 million?
0.811
0.017
7
0.754
0.875
O A. The result is not very close to the actual number of viewers of 4.1 million.
0.834
0.707
O B. The result is very close to the actual number of viewers of 4.1 million.
0.666
0.798
10
0.632
0.765
Oc. The result is exactly the same as the actual number of viewers of 4.1 million.
11
0.735
0.602
O D. The result does not make sense given the context of the data
12
0.576
0.708
13
0.553
0.684
14
0.532
0.601
15
0.514
0.641
16
0.497
0.623
17
0.482
0.606
18
0.468
0.590
0.575
0.561
19
0.456
20
0.444
25
30
35
40
0.396
0.505
0.361
0.483
0.335
0.430
0.312
0.402
45
0.294
0.378
50
0.279
0.361
60
0.254
0.330
70
0.236
0.305
80
0.220
0.286
0.207
0.196
a = 0.05
06
0.269
100
0.256
X = 0.01
n
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